MasterCard Uses AI Machine-Learning Network to Thwart ATM Attacks

MasterCard Inc. says new machine-learning technology has helped it quickly control three separate cyberattacks that targeted automated bank tellers, limiting the damage to about $100,000 each.

The transaction-monitoring system, which also employs data visualization tools, caught the three attacks during the first two months of 2016, according to MasterCard. The company declined to identify the banks.

The Safety Net system, rolled out globally late last year, analyzes more than 1.3 billion transactions per day involving MasterCard debit and credit accounts at banks, merchants and ATMs, using algorithms that assess customer behavior in real-time.

In the three attacks this year, directed against two U.S. banks and one bank in South America, Safety Net identified anomalies such as large cash withdrawals or transactions outside the usual geographic area for a given account. MasterCard notified the banks and rejected transactions, limiting losses to less than $100,000 in each case, said Ajay Bhalla, president of enterprise security solutions at MasterCard. The company declined to identify the banks, citing confidentiality agreements.